Prevalence of Mood and Anxiety Disorders in Individuals at Clinical High Risk for Psychosis: A Comparison with Youth at Risk for Bipolar Disorder

Prevalence of Mood and Anxiety Disorders in Individuals at Clinical High Risk for Psychosis: A Comparison with Youth at Risk for Bipolar Disorder | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 January 2026 V1 Latest version Share on Prevalence of Mood and Anxiety Disorders in Individuals at Clinical High Risk for Psychosis: A Comparison with Youth at Risk for Bipolar Disorder Authors : David Miklowitz 0000-0002-9647-6147 [email protected] , Jean Addington 0000-0002-8298-0756 , Danielle Denenny , Jamie Zinberg , Andrea Auther , Daniel Mathalon , Kristin Cadenhead 0000-0002-5952-4605 , Michelle Friedman-Yakoobian , Scott Woods 0000-0002-3103-5228 , Tyrone Cannon 0000-0002-5632-3154 , Mary O'Brien , and Carrie Bearden Authors Info & Affiliations https://doi.org/10.22541/au.176917688.86373945/v1 161 views 98 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background . Individuals who are at clinical high risk for psychosis (CHR-P) typically present with attenuated positive symptoms. Less is known about the frequencies, breadth, or impact of mood or anxiety disorders that co-occur with CHR-P conditions. Methods . In individuals who met the Structured Interview of Psychosis-Risk Syndromes Criteria for Prodromal Syndromes (N=198; mean age 16.3 + 2.7 yrs), we examined the frequency of mood and anxiety disorders prior to entry into a clinical trial. We compared this sample to youth at high risk for bipolar disorder (N = 127; mean age 13.2 + 2.6) who were also ascertained prior to a clinical trial. Results . Mood disorders were observed in 54.5% of individuals at CHR-P. Individuals with CHR-P and mood disorders had more severe positive and negative symptoms and lower global functioning compared to those at CHR-P without mood disorders. Comparable rates of major depressive disorder (46.5%) and anxiety disorder (67.7%) were observed in CHR-P individuals and youth at high risk for bipolar disorder (58.3% and 59.8%, respectively). With age covaried, individuals at CHR-P were more likely to have social anxiety disorder (24.2%) compared to youth at high risk for bipolar disorder (19.7%) (χ2(1) = 7.61, p = 0.006). Conclusions . Despite different methods of ascertainment, rates of mood and anxiety disorders were similar in these two high-risk populations. Transdiagnostic interventions targeting depression, anxiety, and social-occupational functioning may be especially relevant to high-risk individuals who present with multiple comorbidities. Text: 3,236 words, 3 Tables Prevalence of Mood and Anxiety Disorders in Individuals at Clinical High Risk for Psychosis: A Comparison with Youth at Risk for Bipolar Disorder David J. Miklowitz 1 , Jean M. Addington 2 , Danielle M. Denenny 1 , Jamie L. Zinberg 1 , Andrea M. Auther 3 , Daniel H. Mathalon 4 , Kristin S. Cadenhead 5 , Michelle S. Friedman-Yakoobian 6 , Scott W. Woods 7 , Tyrone D. Cannon 8 , Mary P. O’Brien 8 , Carrie E. Bearden 1 1 Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuropsychiatry and Behavior, University of California, Los Angeles, California, USA 2 Department of Psychiatry, University of Calgary, Calgary, Canada 3 Division of Psychiatry Research, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA 4 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA 5 Department of Psychiatry, University of California, San Diego, La Jolla, California, USA 6 Department of Public Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA 7 Department of Psychiatry, Yale University, New Haven, Connecticut, USA 8 Department of Psychology, Yale University, New Haven, Connecticut, USA Correspondence David J. Miklowitz, Department of Psychiatry and Behavioral Sciences, UCLA Semel Institute, 760 Westwood Plaza Room A8-256, Los Angeles, CA 90095, USA. Email: [email protected] Abstract Background . Individuals who are at clinical high risk for psychosis (CHR-P) typically present with attenuated positive symptoms. Less is known about the frequencies, breadth, or impact of mood or anxiety disorders that co-occur with CHR-P conditions. Methods . In individuals who met the Structured Interview of Psychosis-Risk Syndromes Criteria for Prodromal Syndromes (N=198; mean age 16.3 + 2.7 yrs), we examined the frequency of mood and anxiety disorders prior to entry into a clinical trial. We compared this sample to youth at high risk for bipolar disorder (N = 127; mean age 13.2 + 2.6) who were also ascertained prior to a clinical trial. Results . Mood disorders were observed in 54.5% of individuals at CHR-P. Individuals with CHR-P and mood disorders had more severe positive and negative symptoms and lower global functioning compared to those at CHR-P without mood disorders. Comparable rates of major depressive disorder (46.5%) and anxiety disorder (67.7%) were observed in CHR-P individuals and youth at high risk for bipolar disorder (58.3% and 59.8%, respectively). With age covaried, individuals at CHR-P were more likely to have social anxiety disorder (24.2%) compared to youth at high risk for bipolar disorder (19.7%) (χ2(1) = 7.61, p = 0.006). Conclusions . Despite different methods of ascertainment, rates of mood and anxiety disorders were similar in these two high-risk populations. Transdiagnostic interventions targeting depression, anxiety, and social-occupational functioning may be especially relevant to high-risk individuals who present with multiple comorbidities. 237 words Clinicaltrials.gov trial registration NCT04338152; National Institute of Mental Health grant R01-MH123575 Key words: Early intervention, major depression, psychosocial functioning, comorbidity, subthreshold Introduction In recent years, investigators have defined clinical phenotypes that identify individuals who are at risk for severe mental illnesses such as psychosis. Reliably identifying risk phenotypes in young persons may inform early interventions to prevent or delay the onset of psychosis and other impairing psychiatric syndromes. Individuals with clinical high risk for psychosis (CHR-P) syndrome, characterized by attenuated (subthreshold) positive symptoms (APS), brief intermittent periods of psychosis, and/or genetic risk with functional deterioration have a 16%-30% risk of transitioning to a syndromal psychotic disorder within 2-4 years (Fusar-Poli, Bonoldi et al. 2012; Fusar-Poli and Salazar de Pablo 2022; Cannon, Yu et al. 2016; Carrion, Cornblatt et al. 2016; Koutsouleris, Worthington et al. 2021). Despite the prevalence of CHR-P syndromes in the general population (1.7%) and in clinical samples (19.2%; Salazar de Pablo, Woods et al. 2021), there are relatively few studies focused on the frequency, breadth, or impact of psychiatric conditions that co-occur with psychosis risk syndromes (Rutigliano, Valmaggia et al. 2016). For many individuals with CHR-P, the primary reasons for clinical referral include depression and anxiety, with subthreshold psychotic symptoms identified secondarily through structured interviews (Yung, Phillips et al. 2004; Addington, Cornblatt et al. 2011; Wigman, van Nierop et al. 2012). In a meta-analysis of 312 studies (N =7834), Solmi, Soardo et al. (2023) found that depressive disorders were present in 38% of individuals at CHR-P. In two phases of the multicenter North American Prodrome Longitudinal Study (NAPLS), depressive disorders were present in 41%-48% of CHR-P participants (Addington, Cadenhead et al. 2012; Addington, Liu et al. 2022). Comorbid anxiety disorders were observed in 34%-53% of CHR-P individuals, with social anxiety in up to 42% of cases (Addington, Cadenhead et al. 2012; Addington, Liu et al. 2022; Solmi, Soardo et al. 2023; Hengartner, Heekeren et al. 2017; Kuhney, Damme et al. 2021). Major depression is often the symptom cluster of greatest concern to family members seeking care for an individual with CHR-P because of its association with suicidality, substance misuse and functional impairment (Wigman, van Nierop et al. 2012; Falkenberg, Valmaggia et al. 2015). In longitudinal studies, depressive symptoms contribute to the persistence or recurrence of psychotic symptoms and functional impairment in CHR-P individuals (Yung, Phillips et al. 2004; Bonnett, Hunt et al. 2025; Rutigliano, Valmaggia et al. 2016; Deng, Addington et al. 2021). Aims and Hypotheses In the present study, we examined the prevalence of mood and anxiety disorders in CHR-P youth who were recruited for a multisite clinical trial of family-focused therapy (FFT) (Miklowitz, Addington et al. 2021). We hypothesized that individuals who met the CHR-P criteria with co-occurring mood disorders would have higher levels of positive and negative symptoms, higher levels of concomitant anxiety, and poorer social and occupational functioning compared to those who met the CHR-P criteria without a significant mood component. Although the CHR-P syndrome appears to be relatively specific to the onset of psychosis, its associated symptoms overlap with those seen in populations at risk for other disorders. We would expect CHR-P individuals to have higher rates of depressive and anxiety disorders than the general population (Solmi, Soardo et al. 2023) but it is less clear whether those rates would differ from those in individuals at high risk for bipolar disorder (HR-BD) or other mood disorders. A secondary purpose of this study was to compare the frequency of mood and anxiety disorders in a help-seeking CHR-P sample to a sample of youths at HR-BD who were enrolled in a previous multisite trial of FFT (Miklowitz, Schneck et al. 2020). Why use youth at risk for BD as a comparison sample? Depression is the most common initial presentation of BD in adolescence (O’Donovan and Alda 2020; Duffy, Alda et al. 2007). Offspring of parents with established BD I or II disorders have a 9% chance of developing MDD in childhood and a 35%-45% chance in adolescence (DelBello and Geller 2001; Henin, Biederman et al. 2005; Vandeleur, Rothen et al. 2012; Axelson, Goldstein et al. 2015; Birmaher, Axelson et al. 2009). Less frequent are psychotic-like experiences, which are present in about 15% of offspring of parents with BD (Mendez, Axelson et al. 2019). Offspring of parents with early onset BD I or II who present with depression, anxiety, mood instability, and/or subthreshold manic symptoms have a 49% chance of developing full BD I or II disorder over 8 years (Hafeman, Merranko et al. 2016, Hafeman, Merranko et al. 2017). We hypothesized that individuals at CHR-P and HR-BD – both recruited for psychosocial intervention trials - would have comparable rates of non-bipolar depressive disorders. Although we did not expect group differences in overall rates of anxiety disorders, we explored whether social anxiety disorders were more common among CHR-P individuals given the well-established associations between psychosis (especially suspiciousness and paranoia), social anxiety, and interpersonal avoidance (McAusland, Buchy et al. 2017; Green, Wynn et al. 2024). Social anxiety is also longitudinally associated with lower global functioning in CHR-P individuals (Deng, Addington et al. 2023). Materials and Methods 3.1 Participants and Setting: Clinical High-Risk for Psychosis Sample CHR-P participants were recruited for a single-blind, parallel group RCT comparing FFT to a briefer form of psychoeducational therapy, both administered in 6 months (see full procedures in Miklowitz, Addington et al. 2021). The primary organizational site was the University of California, Los Angeles (UCLA) Semel Institute, with subcontracts to 6 sites of the NAPLS-3 consortium (Addington, Liu et al. 2022). Recruitment occurred from January 20, 2021 to August 9, 2024, with a ssessments conducted remotely due to pandemic restrictions. All participants and parents signed informed assent or consent documents approved by the IRBs at each site. Potential participants were referred by health care providers, educators, or social service agencies or were self-referred in response to online or print announcements. Inclusionary criteria were as follows: (1) age between 12 and 25 years; (2) English speaking; (3) a primary caregiver (most commonly a parent) was willing to consent to the study; and (4) the participant satisfied the Criteria of Psychosis-Risk Syndromes (COPS) based on the Structured Interview of Psychosis-Risk Syndromes (SIPS) and its associated Scale of Psychosis Risk Symptoms (SOPS; McGlashan, Walsh et al. 2010). Participants were ineligible if they (1) met DSM-5 criteria for a current or lifetime psychotic disorder; (2) had a history of impaired intellectual functioning (IQ < 70) or neurological disorder; (3) had a severe substance or alcohol use disorder in the past 6 months; or (4) were currently in family therapy and unwilling to postpone treatment. The intake assessment session consisted of administration of the Structured Clinical Interview for DSM-5 (First, Williams et al. 2015), including all mood, psychosis and anxiety modules. For each case, a consensus of representatives from all 7 sites was obtained on symptom ratings, diagnoses and final eligibility for the trial (see details in Supplement, available online). 3.2 Methods and Procedures The five item ratings on the SOPS rating scale refer to unusual thought content, suspiciousness/persecutory ideas, grandiosity, perceptual abnormalities, and disorganized communication as shown in the prior month. Interrater reliability (intraclass correlations) between site assessors (n=40) for SOPS items ranged from 0.89 to 0.95 (mean=0.91). The Negative Symptom Inventory–Psychosis Risk (NSI-PR; Strauss, Pelletier-Baldelli et al. 2020) consists of 11 items rated on 0–6 scales of severity and covering the prior week. The items reflect the constructs of avolition, anhedonia, blunted affect, asociality, and alogia (poverty of speech content). Research assessors completed a training program in the NSI-PR by Greg Strauss, Ph.D., and met interrater reliability criteria (weighted kappa > 0.80) based on standardized videotape ratings. Current anxiety symptoms were assessed through the Generalized Anxiety Disorder (GAD)-7 scale covering the prior 2 weeks (Spitzer, Kroenke et al. 2006). Additionally, the research assessor made a 0-100 rating on the Social and Occupational Functioning Scale (SOFAS; Rybarczyk, 2018) covering the previous month. 3.3 High-Risk for Bipolar Disorder (HR-BD) Sample The HR-BD study, also a randomized clinical trial of FFT, was conducted at the UCLA Semel Institute (coordinating site), the University of Colorado, Boulder, CO and Anschutz Medical Center, Aurora, CO; and the Stanford University School of Medicine, Stanford, CA. Recruitment commenced on October 6, 2011 and ended on September 15, 2016. Eligible youth were between the ages of 9 years 0 months and 17 years 11 months, met DSM-5 criteria for major depressive disorder or otherwise specified bipolar disorder (based on the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version (KSADS-PL; Chambers, Puig-Antich et al. 1985; Kaufman, Birmaher et al. 2013), and had at least one first-or second-degree relative with a lifetime history of BD (types I or II). Details of the eligibility criteria and enrollment methods are contained in the online supplement. 3.4 Data Analyses We began by tabulating the number of participants with CHR-P who met DSM-5 criteria for a mood disorder (MDD, persistent depressive disorder, unspecified depressive disorder or bipolar spectrum disorder), or any of four anxiety disorders (generalized anxiety, social anxiety, obsessive-compulsive or panic disorder). We explored whether participants with and without mood disorders or anxiety disorders differed on demographic variables (e.g., age, sex, race, ethnicity), SOFAS (functioning) scores, or GAD-7 scores using univariate analyses of variance (ANOVAs) or χ 2 tests. In multivariate ANOVAs, we compared the groups on the five SOPS positive symptom subscales and the five Negative Symptom Inventory subscales, each set considered separately. The second aim concerned the frequency of mood and anxiety disorders in CHR-P individuals compared to HR-BD individuals. Because the samples were obtained using different age criteria (12 to 25 years in CHR-P; 9-17 years in HR-BD), we conducted logistic regression models for binary outcomes (PROC LOGISTIC in SAS 9.4; SAS Institute 2016) in which risk group, age, and their interaction were entered as predictors of the presence/absence of mood or anxiety disorders. As a sensitivity check, we compared the two risk groups on diagnostic frequencies in a subsample with a restricted age range (adolescence, ages 12-17 yrs.). Results 4.1 Demographic variables The CHR sample contained 198 participants (mean 16.3 + 2.7 yrs, range 12-25 yrs; Table 1), 196 (99.0%) of whom met the COPS criteria for attenuated positive symptom syndrome (APSS). Two participants met criteria for brief intermittent psychotic syndrome (1 of whom also met APSS criteria) and 4 for genetic risk and deterioration syndrome (3 of whom also met APSS criteria; see definitions in Table 1). –Insert Table 1 about here— Of 198 participants with CHR-P, 127 (64.1%) met DSM-5 criteria for a current mood disorder: 92 (46.5%) had major depressive disorder, 16 (8.1%) had other (persistent or unspecified) depressive disorder and 19 (9.6%) had bipolar spectrum (types I, II, or unspecified) disorder. The co-diagnosis of CHR-P and any mood disorder was more prevalent among female (86/118, 72.9%) than male participants (41/80, 51.3%; X 2 (1)=9.70, p=0.002) and among Hispanic (42/56, 75.0%) than non-Hispanic (85/142, 59.9%) participants (X 2 (1)=4.0, p=0.046). The co-occurrence of CHR-P with mood disorder was unrelated to age or self-identified race. Youth with CHR-P and a co-occurring mood disorder (n=127) had higher SOPS positive symptom scores than those without a mood disorder (n=71; Wilk’s F[5,185] = 2.76, p=0.02). CHR-P participants with mood disorders also had higher levels of negative symptoms on the five NSI dimensions (Wilk’s F[5,184]=6.11, p<0.0001), higher anxiety scores on the GAD-7 (F[1,163]=11.41, p=0.0009), and lower functioning scores on the SOFAS (F[1,188]=11.02, p= 0.001) compared to CHR-P participants without mood disorders. Covarying age did not change these results. Of the 198 CHR-P participants, 134 (67.7%) had at least one anxiety disorder, with GAD (n=79, 39.9%) and social anxiety disorder (n=48, 24.2%) being the most common. Approximately half of the participants (n=105, 53.0%) had both a mood and an anxiety disorder. Participants with CHR-P and an anxiety disorder were more likely to be female (n=89, 66.4%) (X 2 (1)=8.01, p=0.005), but did not differ from those without an anxiety disorder on age, race or Hispanic ethnicity. Participants with anxiety disorders had higher GAD-7 scores (F[1,172] =12.77, p=0.0005) and non-significantly higher SOPS scores than participants without anxiety disorders (F[5,191]=2.23, p=0.053). The participants with and without anxiety disorders did not differ on negative symptom scores or SOFAS scores. 4.2 Comparing Individuals at CHR-P to Individuals at High-Risk for Bipolar Disorder (HR-BD) The HR-BD sample (N= 127) was, as expected, younger (mean 13.2+2.6 yrs) than the CHR-P sample (mean 16.3+2.7; F[1,321] =104.9, p<0.0001; Table 2). The samples did not differ in gender distribution or parental education. The CHR-P sample was more diverse in self-reported race and ethnicity than the HR-BD sample (Table 2). –Insert Table 2 about here– Diagnoses based on the SCID (CHR-P sample) and KSADS-PL (HR-BD sample) are given in Table 3. By design, the HR-BD sample had a larger proportion of participants with bipolar spectrum disorder (n=52, 40.9%) than the CHR-P sample (n=19, 9.6%). In a logistic regression model, there was no effect of risk group, age, or their interaction on the frequency of non-bipolar depressive disorders (CHR-P sample, n=108, 54.5%; HR-BD sample, n=75, 59.1%). Rates of MDD were comparable in the CHR-P (n=92, 46.5%) and HR-BD (n=74, 58.3%) samples. Overall, MDD was more common in older than younger participants (X 2 (1)=6.19, p=0.01). –Insert Table 3 about here– Of the 198 CHR-P participants, 134 (67.7%) met DSM-5 criteria (using the SCID) for an anxiety disorder, compared to 76 (59.8%) in the HR-BD sample (based on the KSADS-PL), a nonsignificant difference. In a logistic regression model, there was a positive association between age and the likelihood of having GAD (χ 2 (1)=5.80, p=0.016) but there was no effect of risk group or risk group by age interaction on GAD diagnoses. With age covaried, there was a higher rate of social anxiety disorder in the CHR-P risk group (n=48, 24.2%) compared to the HR-BD group (n=25, 19.7%; X2(1)=7.61, p=0.006); and an age by risk group interaction, indicating a higher frequency of social anxiety disorders in older CHR-P participants (X 2 (1)=6.96, p=0.008). There were no effects of risk group on the frequencies of obsessive compulsive disorder or panic disorder (Table 3). Finally, we examined rates of non-bipolar depressive disorders and anxiety disorders in adolescent participants (age restricted to 12-17 years; CHR-P, n=104; HR-BD, n=85). There were no effects of risk group, age, or their interaction on rates of depressive or anxiety disorders in this subset. Discussion Across studies, mood and anxiety disorders have been observed in at least 50% of youth at risk for psychotic disorders (McAusland, Buchy et al. 2017; Solmi, Soardo et al. 2023). In this sample of help-seeking adolescents and young adults at CHR-P, mood disorders were present in 64%: Approximately half (46.5%) had MDD and 18% had other forms of depression or bipolar spectrum disorders. The rate of non-bipolar depressive disorders in CHR-P (54.5%) was comparable to the rate observed in symptomatic children and adolescents with a family history of bipolar disorder (59.1%). Bipolar spectrum disorders were more common in individuals at HR-BD (40.9%) than in individuals at CHR-P (9.6%), reflecting differences in trial enrollment requirements (see online supplement). We acknowledge that some degree of overlap between these two high-risk populations would be expected given that both were treatment-seeking and had some degree of functional impairment. The diagnostic frequencies were comparable to rates observed in other studies of CHR-P individuals (Addington, Cadenhead et al. 2012; Addington, Liu et al. 2022; Solmi, Soardo et al. 2023). Although overall rates of anxiety disorders were comparable in the two groups, rates of social anxiety disorder were elevated in the CHR-P group (24.2%) compared to the HR-BD group (19.7%), with higher rates among older CHR-P participants. In a prior longitudinal study of CHR-P, individuals with sustained social anxiety had lower global functioning over 2 years, despite positive symptoms having abated (Deng, Addington et al., 2023). Youth at CHR-P with mood disorders had higher levels of negative symptoms and lower social and occupational functioning than CHR-P youth without mood disorders. An individual participant meta-analysis of CHR-P studies concluded that symptoms of depression were associated with psychosis onset, independently of attenuated psychosis symptoms, declines in functioning, or negative symptoms (Bonnett, Hunt et al. 2025). Depressive and anxiety disorders may characterize the subgroup of CHR-P individuals who have persistent levels of psychosocial disability (Addington, Cornblatt et al. 2011; Devoe, Braun et al. 2020). Interventions that emphasize mood and anxiety management may be important supplements to existing prevention programs for CHR-P, even among those individuals who do not transition to full psychosis. The clusters of symptoms that define the CHR-P and HR-BD syndromes tend to have high rates of false positive predictions for the outcome of conversion. Over a 10-year period, individuals who met CHR-P criteria transitioned to psychosis in 35% of cases (Nelson, Yuen et al. 2013, Salazar de Pablo, Woods et al. 2021). In offspring of parents with BD, optimized prediction of BD onset is 49% over 8 years (Hafeman, Merranko et al. 2016). Nonetheless, high-risk youth who do not convert often have adverse outcomes. In a 3-5 year follow-up of CHR-P individuals who did not convert to psychosis, 40%-45% had impaired social and role functioning ( Addington, Cornblatt et al. 2011, Carrion, McLaughlin et al. 2013). In follow-ups over 2-5 years, HR-BD youth achieved extended remissions in only 25%-30% of cases (Birmaher, Gill et al. 2014; Weintraub, Schneck et al. 2020). Understanding the features of high-risk youth who do and do not convert will help clarify the subpopulations that are most likely to benefit from early interventions. Limitations In the present study we compared late adolescent/young adults with CHR-P to children and adolescents with HR-BD, reflecting differences in the onset of prodromal symptoms in the two populations. Further, the diagnostic instruments typically used in studies of CHR- and HR-BD samples, although similar in symptom coverage, use different diagnostic consensus methods: for the SCID and SIPS, consensus is made among a team of experts, whereas for the KSADS-PL, consensus is derived from separate youth and parent interviews. Comparing high-risk populations that are matched on age, age at symptom onset and ascertainment methods may yield different conclusions regarding frequencies of co-occurring disorders. The cross-sectional design of this study did not enable us to test whether mood or anxiety symptoms reflect reactions to paranoia, suspiciousness or unusual thoughts, or whether depressive or anxiety symptoms increase attentional biases toward threat, contributing to the vulnerability to psychotic symptoms (Freeman and Fowler 2009; Deng, Addington et al. 2023). Additionally, both high-risk groups are best characterized as “samples of inconvenience” (Kroupin, Henrich et al. 2025) that were recruited based on specific symptom and functional criteria that emerged from structured interviews. Thus, the generalizability of the results to population samples is uncertain. Notably, the rates of mood and anxiety disorders in a large clinic sample of outpatients with CHR-P were higher than those observed in the present study (West, Parrish et al. 2022). Conclusion The characteristics of adolescents or young adults who are in the early phases of psychosis or bipolar disorder have interested researchers since at least the 1950s (e.g., (Arieti, 1955). Our current methods of ascertaining high-risk populations use reliable and well-validated instrumentation, including calculators that estimate risk at an individual level (e.g., Cannon, Yu et al. 2016; Hafeman, Merranko et al. 2017; Birmaher, Merranko et al. 2018). We are limited by the sensitivity and specificity of these methods of prediction. Nonetheless, the observation of comparable rates of mood and anxiety disorders across CHR-P and HR-BD individuals supports the utility of transdiagnostic early-intervention approaches —particularly interventions targeting depression, anxiety, and functioning—regardless of whether the eventual outcome is psychosis or bipolar disorder. Author Statements Funding This study was supported by grant R01-MH123575 to Dr. Miklowitz from the National Institute of Mental Health. The funding source had no role in the design or conduct of the study; collection, management, analysis and interpretation of data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Ethics Statement The study was approved by the Medical-3 Institutional Review Board at the David Geffen School of Medicine at UCLA (IRB of record) and the individual IRBs at the Division of Psychiatry Research, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA; Department of Psychiatry, University of California, San Diego, La Jolla, California, USA; Department of Public Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; Department of Psychiatry, Yale University School of Medicine, and Department of Psychiatry, University of Calgary, Calgary, Canada. Participants and family members received oral instructions about the study’s aims, risks, and benefits and reviewed and signed written consent or assent forms prior to taking part in study procedures. Conflicts of Interest Dr. Miklowitz receives research support from the National Institute of Mental Health (NIMH), the Baszucki Brain Research Fund, Milken Foundation, Attias Family Foundation, Max Gray Fund; and the Negeen Foundation; and book royalties from Guilford Press and John Wiley and Sons. None of the other authors report any conflicts of interest. Data Availability Statement Data is available from the corresponding author upon reasonable request. ORCID David J. Miklowitz, 0000 0002 9647 6147 Jean M. Addington, 0000-0002-8298-0756 Jamie Zinberg, 0000-0002-6241-1484 Danielle M. Denenny, 0000-0001-6707-677X Andrea M. Auther, 0000-0001-6511-9596 Daniel H. Mathalon, 0000-0001-6090-4974 Kristin S. Cadenhead, 0000-0002-5952-4605 Michelle S. Friedman-Yakoobian, 0000-0001-7354-1818 Scott W. Woods, 0000-0002-3103-5228 Tyrone P. Cannon, 0000-0002-5632-3154 Mary P. O’Brien, 0009-0009-1662-9632 Carrie E. Bearden, 0000-0002-8516-923X References Addington, J., K. S. Cadenhead, B. A. Cornblatt, D. H. Mathalon, T. H. McGlashan, D. O. Perkins, L. J. Seidman, M. T. Tsuang, E. F. Walker, S. W. Woods, J. A. Addington and T. D. Cannon (2012). ”North American Prodrome Longitudinal Study (NAPLS 2): overview and recruitment.” Schizophrenia Research 142 (1-3): 77-82. Addington, J., B. A. Cornblatt, K. S. Cadenhead, T. D. Cannon, T. H. McGlashan, D. O. Perkins, L. J. Seidman, M. T. Tsuang, E. F. Walker, S. W. Woods and R. Heinssen (2011). ”At clinical high risk for psychosis: outcome for nonconverters.” American Journal of Psychiatry 168 (8): 800-805. Addington, J., L. Liu, K. Brummitt, C. E. Bearden, K. S. Cadenhead, B. A. Cornblatt, M. Keshavan, D. H. Mathalon, T. H. McGlashan, D. O. Perkins, L. J. Seidman, W. Stone, M. T. Tsuang, E. F. Walker, S. W. Woods and T. D. Cannon (2022). ”North American Prodrome Longitudinal Study (NAPLS 3): Methods and baseline description.” Schizophrenia Research 243 : 262-267. Arieti, S. (1955). Interpretation of Schizophrenia . New York, Robert Brunner, Inc. Axelson, D. A., B. Goldstein, T. Goldstein, K. Monk, H. Yu, M. B. Hickey, D. Sakolsky, R. Diler, D. Hafeman, J. Merranko, S. Iyengar, D. Brent, D. Kupfer and B. Birmaher (2015). ”Diagnostic precursors to bipolar disorder among offspring of parents with bipolar disorder: a longitudinal study.” American Journal of Psychiatry 172 (7): 638-646. Birmaher, B., D. Axelson, K. Monk, C. Kalas, B. Goldstein, M. B. Hickey, M. Obreja, M. Ehmann, S. Iyengar, W. Shamseddeen, D. Kupfer and B. D. (2009). ”Lifetime psychiatric disorders in school-aged offspring of parents with bipolar disorder: the Pittsburgh Bipolar Offspring study.” Archives of General Psychiatry 66 (3): 287-296. Birmaher, B., M. K. Gill, D. A. Axelson, B. I. Goldstein, T. R. Goldstein, H. Yu, F. Liao, S. Iyengar, R. S. Diler, M. Strober, H. Hower, S. Yen, J. Hunt, J. A. Merranko, N. D. Ryan and M. B. Keller (2014). ”Longitudinal trajectories and associated baseline predictors in youths with bipolar spectrum disorders.” American Journal of Psychiatry 171 (9): 990-999. Birmaher, B., J. A. Merranko, T. R. Goldstein, M. K. Gill, B. I. Goldstein, H. Hower, S. Yen, D. Hafeman, M. Strober, R. S. Diler, D. Axelson, N. D. Ryan and M. B. Keller (2018). ”A risk calculator to predict the individual risk of conversion from subthreshold bipolar symptoms to bipolar disorder I or II in youth.” Journal of the American Academy of Child and Adolescent Psychiatry 57 (10): 755-763. Bonnett, L. J., A. Hunt, A. Flores, C. Tudur Smith, F. Varese, R. Byrne, H. Law, M. Milicevic, R. Carney, S. Parker, A. R. Yung and I. S. Group (2025). ”Clinical prediction model for transition to psychosis in individuals meeting At Risk Mental State criteria.” Schizophrenia (Heidelb) 11 (1): 29. Cannon, T. D., C. Yu, J. Addington, C. E. Bearden, K. S. Cadenhead, B. A. Cornblatt, R. Heinssen, C. D. Jeffries, D. H. Mathalon, T. H. McGlashan, D. O. Perkins, L. J. Seidman, M. T. Tsuang, E. F. Walker, S. W. Woods and M. W. Kattan (2016). ”An Individualized Risk Calculator for Research in Prodromal Psychosis.” American Journal of Psychiatry 173 (10): 980-988. Carrion, R. E., B. A. Cornblatt, C. Z. Burton, A. M. Auther, S. Adelsheim, R. Calkins, C. S. Carter, T. Niendam, T. G. Sale, S. F. Taylor, W. R. McFarlane and I. F. Tso (2016). ”Personalized Prediction of Psychosis: External Validation of the NAPLS-2 Psychosis Risk Calculator With the EDIPPP Project.” American Journal of Psychiatry 173 (10): 989-996. Carrion, R. E., D. McLaughlin, T. E. Goldberg, A. M. Auther, R. H. Olsen, D. M. Olvet, C. U. Correll and B. A. Cornblatt (2013). ”Prediction of functional outcome in individuals at clinical high risk for psychosis.” JAMA Psychiatry 70 (11): 1133-1142. Chambers, W. J., J. Puig-Antich, M. Hirsch, P. Paez, P. J. Ambrosini, M. A. Tabrizi and M. Davies (1985). ”The assessment of affective disorders in children and adolescents by semi-structured interview: test-retest reliability.” Archives of General Psychiatry 42 : 696-702. DelBello, M. P. and B. Geller (2001). ”Review of studies of child and adolescent offspring of bipolar parents.” Bipolar Disorders 3 (6): 325-334. Deng, W., J. Addington, C. E. Bearden, K. S. Cadenhead, B. A. Cornblatt, D. H. Mathalon, T. H. McGlashan, D. O. Perkins, L. J. Seidman, M. T. Tsuang, S. W. Woods, E. F. Walker, J. Joormann and T. Cannon (2021). ”Depression Predicts Global Functional Outcomes in Individuals at Clinical High Risk for Psychosis.” Psychiatry Research and Clinical Practice 3 (4): 163-171. Deng, W., J. Addington, C. E. Bearden, K. S. Cadenhead, B. A. Cornblatt, D. H. Mathalon, D. O. Perkins, L. J. Seidman, M. T. Tsuang, S. W. Woods, E. F. Walker and T. D. Cannon (2023). ”Characterizing sustained social anxiety in individuals at clinical high risk for psychosis: trajectory, risk factors, and functional outcomes.” Psychological Medicine 53 (8): 3644-3651. Devoe, D. J., A. Braun, T. Seredynski and J. Addington (2020). ”Negative Symptoms and Functioning in Youth at Risk of Psychosis: A Systematic Review and Meta-analysis.” Harvard Review of Psychiatry 28 (6): 341-355. Duffy, A., M. Alda, L. Crawford, R. Milin and P. Grof (2007). ”The early manifestations of bipolar disorder: a longitudinal prospective study of the offspring of bipolar parents.” Bipolar Disorders 9 (8): 828-838. Falkenberg, I., L. Valmaggia, M. Byrnes, M. Frascarelli, C. Jones, M. Rocchetti, B. Straube, S. Badger, P. McGuire and P. Fusar-Poli (2015). ”Why are help-seeking subjects at ultra-high risk for psychosis help-seeking?” Psychiatry Research 228 (3): 808-815. First, M. B., J. B. Williams, L. S. Benjamin and R. L. Spitzer (2015). “Structured Clinical Interview for DSM-5 (SCID-V, Research Version).” Arlington, VA, American Psychiatric Association. Freeman, D. and D. Fowler (2009). ”Routes to psychotic symptoms: trauma, anxiety and psychosis-like experiences.” Psychiatry Research 169 (2): 107-112. Fusar-Poli, P., I. Bonoldi, A. R. Yung, S. Borgwardt, M. J. Kempton, L. Valmaggia, F. Barale, E. Caverzasi and P. McGuire (2012). ”Predicting psychosis: meta-analysis of transition outcomes in individuals at high clinical risk.” Archives of General Psychiatry 69 (3): 220-229. Fusar-Poli, P. and G. Salazar de Pablo (2022). ”No Meta-analytic Effect of Age on Probability of Developing Psychosis in Individuals at Clinical High Risk.” Journal of the American Academy of Child and Adolescent Psychiatry 61 (6): 731-732. Green, M. F., J. K. Wynn, N. I. Eisenberger, W. P. Horan, J. Lee, A. McCleery, D. J. Miklowitz, E. A. Reavis and L. F. Reddy (2024). ”Social cognition and social motivation in schizophrenia and bipolar disorder: are impairments linked to the disorder or to being socially isolated?” Psychol Medicine 54 (9): 2015-2023. Hafeman, D. M., J. Merranko, D. Axelson, B. I. Goldstein, T. Goldstein, K. Monk, M. B. Hickey, D. Sakolsky, R. Diler, S. Iyengar, D. Brent, D. Kupfer and B. Birmaher (2016). ”Toward the definition of a bipolar prodrome: dimensional predictors of bipolar spectrum disorders in at-risk youths.” American Journal of Psychiatry 173 (7): 695-704. Hafeman, D. M., J. Merranko, T. R. Goldstein, D. Axelson, B. I. Goldstein, K. Monk, M. B. Hickey, D. Sakolsky, R. Diler, S. Iyengar, D. A. Brent, D. J. Kupfer, M. W. Kattan and B. Birmaher (2017). ”Assessment of a person-level risk calculator to predict new-onset bipolar spectrum disorder in youth at familial risk.” JAMA Psychiatry 74 (8): 841-847. Hengartner, M. P., K. Heekeren, D. Dvorsky, S. Walitza, W. Rossler and A. Theodoridou (2017). ”Checking the predictive accuracy of basic symptoms against ultra high-risk criteria and testing of a multivariable prediction model: Evidence from a prospective three-year observational study of persons at clinical high-risk for psychosis.” European Psychiatry 45 : 27-35. Henin, A., J. Biederman, E. Mick, G. S. Sachs, D. R. Hirshfeld-Becker, R. S. Siegel, S. McMurrich, L. Grandin and A. A. Nierenberg (2005). ”Psychopathology in the offspring of parents with bipolar disorder: a controlled study.” Biological Psychiatry 58 (7): 554-561. Kaufman, J., B. Birmaher, D. Axelson, F. Perepletchikova, D. Brent and N. Ryan (2013). “Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version, 2013 (K-SADS-PL 2013).” Western Psychiatric Institute and Clinic, Pittsburgh, PA. . Koutsouleris, N., M. Worthington, D. B. Dwyer, L. Kambeitz-Ilankovic, R. Sanfelici, P. Fusar-Poli, M. Rosen, S. Ruhrmann, A. Anticevic, J. Addington, D. O. Perkins, C. E. Bearden, B. A. Cornblatt, K. S. Cadenhead, D. H. Mathalon, T. McGlashan, L. Seidman, M. Tsuang, E. F. Walker, S. W. Woods, P. Falkai, R. Lencer, A. Bertolino, J. Kambeitz, F. Schultze-Lutter, E. Meisenzahl, R. K. R. Salokangas, J. Hietala, P. Brambilla, R. Upthegrove, S. Borgwardt, S. Wood, R. E. Gur, P. McGuire and T. D. Cannon (2021). ”Toward Generalizable and Transdiagnostic Tools for Psychosis Prediction: An Independent Validation and Improvement of the NAPLS-2 Risk Calculator in the Multisite PRONIA Cohort.” Biological Psychiatry 90 (9): 632-642. Kroupin, I., J. Henrich and M. Muthukrishna (2025). ”Inconvenience and generalization in building a better psychology: Commentary on Sherman (2025).” Amercan Psychologist 80 (7): 1081-1085. Kuhney, F. S., K. S. F. Damme, A. Pelletier-Baldelli, C. Chun, L. M. Ellman, J. Schiffman and V. A. Mittal (2021). ”Prevalence and Functional Consequences of Social Anxiety in Individuals at Clinical High-Risk for Psychosis: Perspective From a Community Sample Comparison.” Schizophrenia Bulletin Open 2 (1): sgab025. McAusland, L., L. Buchy, K. S. Cadenhead, T. D. Cannon, B. A. Cornblatt, R. Heinssen, T. H. McGlashan, D. O. Perkins, L. J. Seidman, M. T. Tsuang, E. F. Walker, S. W. Woods, C. E. Bearden, D. H. Mathalon and J. Addington (2017). ”Anxiety in youth at clinical high risk for psychosis.” Early Intervention in Psychiatry 11 (6): 480-487. McGlashan, T., B. C. Walsh and S. W. Woods (2010). “The Psychosis Risk Syndrome: Handbook for Diagnosis and Follow-Up.” New York, Oxford University Press. Mendez, I., D. Axelson, J. Castro-Fornieles, D. Hafeman, T. R. Goldstein, B. I. Goldstein, R. Diler, R. Borras, J. Merranko, K. Monk, M. B. Hickey and B. Birmaher (2019). ”Psychotic-Like Experiences in Offspring of Parents With Bipolar Disorder and Community Controls: A Longitudinal Study.” Journal of the American Academy of Child and Adolescent Psychiatry 58 (5): 534-543 e536. Miklowitz, D. J., J. M. Addington, M. P. O’Brien, D. M. Denenny, M. J. Weintraub, J. L. Zinberg, D. H. Mathalon, B. A. Cornblatt, M. S. Friedman-Yakoobian, W. S. Stone, K. S. Cadenhead, S. W. Woods, C. A. Sugar, T. D. Cannon and C. E. Bearden (2021). ”Family-focused therapy for individuals at high clinical risk for psychosis: A confirmatory efficacy trial.” Early Intervention in Psychiatry , 16 (6):632-642. Miklowitz, D. J., C. D. Schneck, P. D. Walshaw, M. K. Singh, A. E. Sullivan, R. L. Suddath, M. Forgey Borlik, C. A. Sugar and K. D. Chang (2020). ”Effects of Family-Focused Therapy vs Enhanced Usual Care for Symptomatic Youths at High Risk for Bipolar Disorder: A Randomized Clinical Trial.” JAMA Psychiatry 77 (5): 455-463. Nelson, B., H. P. Yuen, S. J. Wood, A. Lin, D. Spiliotacopoulos, A. Bruxner, C. Broussard, M. Simmons, D. L. Foley, W. J. Brewer, S. M. Francey, G. P. Amminger, A. Thompson, P. D. McGorry and A. R. Yung (2013). ”Long-term follow-up of a group at ultra high risk (”prodromal”) for psychosis: the PACE 400 study.” JAMA Psychiatry 70 (8): 793-802. O’Donovan, C. and M. Alda (2020). ”Depression Preceding Diagnosis of Bipolar Disorder.” Frontiers in Psychiatry 11 : 500. Rutigliano, G., L. Valmaggia, P. Landi, M. Frascarelli, M. Cappucciati, V. Sear, M. Rocchetti, A. De Micheli, C. Jones, E. Palombini, P. McGuire and P. Fusar-Poli (2016). ”Persistence or recurrence of non-psychotic comorbid mental disorders associated with 6-year poor functional outcomes in patients at ultra high risk for psychosis.” Journal of Affective Disorders 203 : 101-110. Rybarczyk, B. (2018). “Social and Occupational Functioning Assessment Scale (SOFAS)”. Encyclopedia of Clinical Neuropsychology. J. S. Kreutzer, DeLuca, J., Caplan, B. . Cham, Springer : 3206-3206. Salazar de Pablo, G., S. W. Woods, G. Drymonitou, H. de Diego and P. Fusar-Poli (2021). ”Prevalence of Individuals at Clinical High-Risk of Psychosis in the General Population and Clinical Samples: Systematic Review and Meta-Analysis.” Brain Science 11 (11). SAS Institute, I. (2016). “Base SAS 9.4 Procedures Guide: Statistical Procedures, Fifth Edition.” Cary, N.C., SAS Institute, Inc. Solmi, M., L. Soardo, S. Kaur, M. Azis, A. Cabras, M. Censori, L. Fausti, F. Besana, G. Salazar de Pablo and P. Fusar-Poli (2023). ”Meta-analytic prevalence of comorbid mental disorders in individuals at clinical high risk of psychosis: the case for transdiagnostic assessment.” Molecular Psychiatry 28 (6): 2291-2300. Spitzer, R. L., K. Kroenke, J. B. Williams and B. Lowe (2006). ”A brief measure for assessing generalized anxiety disorder: the GAD-7.” Archives of Internal Medicine 166 (10): 1092-1097. Strauss, G. P., A. Pelletier-Baldelli, K. F. Visser, E. F. Walker and V. A. Mittal (2020). ”A review of negative symptom assessment strategies in youth at clinical high-risk for psychosis.” Schizophrenia Research 222 : 104-112. Vandeleur, C., S. Rothen, M. Gholam-Rezaee, E. Castelao, S. Vidal, S. Favre, F. Ferrero, O. Halfon, P. Fumeaux, K. R. Merikangas, J. M. Aubry, M. Burstein and M. Preisig (2012). ”Mental disorders in offspring of parents with bipolar and major depressive disorders.” Bipolar Disorders 14 (6): 641-653. Weintraub, M. J., C. D. Schneck, P. D. Walshaw, K. D. Chang, A. E. Sullivan, M. K. Singh and D. J. Miklowitz (2020). ”Longitudinal trajectories of mood symptoms and global functioning in youth at high risk for bipolar disorder.” Journal of Affective Disorders 277 : 394-401. West, M. L., E. M. Parrish and M. Friedman-Yakoobian (2022). ”Treatment outcomes for young people at clinical high risk for psychosis: Data from a specialized clinic.” Early Intervention in Psychiatry 16 (5): 500-508. Wigman, J. T., M. van Nierop, W. A. Vollebergh, R. Lieb, K. Beesdo-Baum, H. U. Wittchen and J. van Os (2012). ”Evidence that psychotic symptoms are prevalent in disorders of anxiety and depression, impacting on illness onset, risk, and severity–implications for diagnosis and ultra-high risk research.” Schizophrenia Bulletin 38 (2): 247-257. Yung, A. R., L. J. Phillips, H. P. Yuen and P. D. McGorry (2004). ”Risk factors for psychosis in an ultra high-risk group: psychopathology and clinical features.” Schizophrenia Research 67 (2-3): 131-142. Age (Yrs.) 16.3 (2.7) 12 to 25 Sex at birth, no. (%) female 118 (59.6) Criteria for Psychosis Risk Syndrome subtype Attenuated positive symptoms (APS) Current progression Current persistance Current partial remission Brief intermittent psychotic symptoms (BIPS) BIPS alone BIPS with APS (progression) Genetic risk and deterioration (GRD) GRD alone GRD with APS (progression) GRD with APS (persistence) First-degree relative with psychosis Missing 196 (99.0) 163 (82.3) 31 (15.7) 2 (1.0) 2 (0.5) 1 (0.5) 1 (0.5) 4 (2.0) 1 (0.5) 2 (1.0) 1 (0.5) 11 (5.6) 1 (0.5) Scale for Psychosis Risk Symptoms (SOPS) Scores (1-6 scales) Unusual Thought Content 3.6 (1.2) 0 – 6 Suspiciousness/Persecutory Ideas 3.1 (1.6) 0 – 6 Grandiose ideas 0.8 (1.3) 0 – 5 Perceptual abnormalities 3.4 (1.4) 0 – 5 Disorganized communication 1.8 (1.4) 0 – 6 Total score 12.7 (3.7) 2 – 23 Negative Symptom Inventory – Psychosis Risk Anhedonia 4.5 (2.9) 0 – 18 Avolition 4.3 (2.6) 0 – 10 Asociality 7.1 (3.9) 0 – 15 Blunted affect 4.6 (4.4) 0 – 20 Alogia 1.1 (1.3) 0 - 5 Generalized Anxiety Disorder-7 11.7 (5.7) 0 - 21 Social and Occupational Functioning Scale 57.7 (16.5) 20 - 95 Notes: APS persistence = subthreshold psychotic symptoms have been ongoing but have not worsened in the last 12 months; APS Progression = subthreshold psychotic symptoms have emerged or worsened within the last year. APS Partial remission = previously qualifying symptoms have improved (i.e., not met frequency criteria) for 6 months or less. Individuals with brief intermittent psychotic disorder may have had scores of 6 on individual APS items and still met study eligibility criteria. Age, mean + SD 16.3 (2.7) 13.2 (2.6) p < 0.0001 Sex at birth (no. (%) female) 118 (59.6) 82 (64.6) 0.37 Race Black/African American Asian/Pacific Islander Native American/First Nations White More than one race Native Hawaiian/Pacific Islander Other/unknown 9 (4.5) 21 (10.6) 11 (5.6) 108 (54.5) 48 (24.2) 0 (0.0) 1 (0.5) 7 (5.5) 4 (3.1) 1 (0.8) 103 (81.1) 10 (7.9) 2 (1.6) 0 (0.0) 0.0001 Ethnicity, Hispanic (no., %) 56 (28.3) 23 (18.1) 0.037 Education, participant, yrs (SD) 9.8 (2.2) 7.0 (2.7) 0.0001 Education, highest parental level, no. (%) Pre-baccalaureate College degree Post-Baccalaureate Graduate degree Missing 48 (24.2) 69 (34.8) 10 (5.0) 69 (34.8) 2 (1.0) 26 (20.5) 33 (26.0) 11 (8.7) 47 (37.0) 10 (7.9) 0.29 DSM-5 Diagnosis Any mood disorder, current Major depressive disorder Single episode Recurrent Other depressive disorder 1 Bipolar and related disorders Bipolar I Bipolar II Bipolar disorder, otherwise specified Cyclothymic disorder Any anxiety disorder, current Generalized anxiety disorder, current, no. (%) Social anxiety disorder, current, no. (%) Obsessive-compulsive disorder, current, no. (%) Panic disorder, current (no., %) 127 (64.1) 92 (46.5) 45 (22.7) 47 (23.7) 16 (8.1) 19 (9.6) 6 (3.0) 6 (3.0) 4 (2.0) 3 (1.5) 134 (67.7) 79 (39.9) 48 (24.2) 40 (20.2) 16 (8.1) 127 (100.0) 74 (58.3) 21 (16.5) 53 (41.7) 1 (0.08) 52 (40.9) 0 (0.0) 0 (0.0) 52 (40.9) 0 76 (59.8) 62 (48.8) 25 (19.7) 14 (11.0) 6 (4.7) 0.0001 0.04 0.007 0.004 0.0001 0.15 0.11 0.34 0.03 0.24 0.94 0.82 0.80 0.45 0.13 0.45 0.32 0.006 0.45 0.47 0.99 0.01 0.07 0.86 0.07 0.001 0.02 0.76 0.21 0.15 0.99 0.39 0.39 0.73 0.47 0.39 0.64 0.008 0.33 0.51 1 Includes persistent depressive disorder and unspecified depressive disorder. Information & Authors Information Version history V1 Version 1 23 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords comorbidity early intervention major depression psychosocial functioning subthreshold Authors Affiliations David Miklowitz 0000-0002-9647-6147 [email protected] University of California Los Angeles Department of Psychiatry and Biobehavioral Sciences View all articles by this author Jean Addington 0000-0002-8298-0756 University of Calgary Department of Psychiatry View all articles by this author Danielle Denenny University of California Los Angeles Department of Psychiatry and Biobehavioral Sciences View all articles by this author Jamie Zinberg University of California Los Angeles Department of Psychiatry and Biobehavioral Sciences View all articles by this author Andrea Auther Donald and Barbara Zucker School of Medicine at Hofstra/Northwell View all articles by this author Daniel Mathalon University of California San Francisco Department of Psychiatry and Behavioral Sciences View all articles by this author Kristin Cadenhead 0000-0002-5952-4605 University of California San Diego Department of Psychiatry View all articles by this author Michelle Friedman-Yakoobian Beth Israel Deaconess Medical Center Agoos Medical Library View all articles by this author Scott Woods 0000-0002-3103-5228 Yale School of Medicine Department of Psychiatry View all articles by this author Tyrone Cannon 0000-0002-5632-3154 Yale University Department of Psychology View all articles by this author Mary O'Brien Yale University Department of Psychology View all articles by this author Carrie Bearden University of California Los Angeles Department of Psychiatry and Biobehavioral Sciences View all articles by this author Metrics & Citations Metrics Article Usage 161 views 98 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation David Miklowitz, Jean Addington, Danielle Denenny, et al. Prevalence of Mood and Anxiety Disorders in Individuals at Clinical High Risk for Psychosis: A Comparison with Youth at Risk for Bipolar Disorder. Authorea . 23 January 2026. DOI: https://doi.org/10.22541/au.176917688.86373945/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); Cited by Matthias Nieberler, Miriam Appel, Catherina Klüpfel, Wiebke Warrings, Sarah Kittel-Schneider, Alles bipolar oder was? Differenzialdiagnostische Einordnung von Stimmungsschwankungen im jungen Erwachsenenalter, Der Nervenarzt, (2026). https://doi.org/10.1007/s00115-026-01970-7 Crossref Loading... View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.176917688.86373945/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fdf94833ea20db4',t:'MTc3OTE1Njc4Mg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();